File size: 2,331 Bytes
e49d385 45dbe70 e49d385 45dbe70 e49d385 45dbe70 e49d385 45dbe70 e49d385 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 |
---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mtop
model-index:
- name: t5-base-pointer-mtop
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-base-pointer-mtop
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the mtop dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1131
- Exact Match: 0.7199
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 1.7749 | 6.65 | 200 | 0.5892 | 0.0031 |
| 0.6021 | 13.33 | 400 | 0.5160 | 0.0139 |
| 0.6044 | 19.98 | 600 | 0.4080 | 0.0532 |
| 0.3302 | 26.65 | 800 | 0.1865 | 0.3620 |
| 0.1483 | 33.33 | 1000 | 0.1267 | 0.5105 |
| 0.0768 | 39.98 | 1200 | 0.1131 | 0.5298 |
| 0.0525 | 46.65 | 1400 | 0.1219 | 0.5414 |
| 0.0801 | 53.33 | 1600 | 0.1186 | 0.5275 |
| 0.0331 | 59.98 | 1800 | 0.1306 | 0.5423 |
| 0.0254 | 66.65 | 2000 | 0.1396 | 0.5396 |
| 0.0168 | 73.33 | 2200 | 0.1560 | 0.5436 |
| 0.0129 | 79.98 | 2400 | 0.1659 | 0.5494 |
| 0.0105 | 86.65 | 2600 | 0.1699 | 0.5423 |
| 0.0088 | 93.33 | 2800 | 0.1742 | 0.5472 |
| 0.0077 | 99.98 | 3000 | 0.1775 | 0.5468 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
|